Every detector in an electronic image sensor, such as a CCD image sensor, may have a different response function that relates the input intensity of light (or other electromagnetic radiation) to a pixel value in the digital image. This response function can change with time or operating temperature. Image sensors are calibrated such that each detector has the same response for the same input intensity (illumination radiance). The calibration is generally performed by illuminating each detector with a given radiance from a calibration lamp and then recording the signal from each detector to estimate the response function of the detector. The response function for each detector is used to equalize the output of all of the detectors such that a uniform illumination across all of the detectors will produce a uniform output.
FIG. 1 shows a schematic of an image acquired by a linear image sensing arrays. In such an image, if errors in estimating the response curve of a detector are different from the errors in the response curve of an adjacent detector, the detector responses will not be equalized and streaking 2 will appear in the image along the scan direction indicated by arrow A. Often to achieve a very long array, several image sensor chips are joined together to form a single linear image sensor. When calibration errors occur between chips, the streaking is generally referred to as banding, as illustrated at reference numeral 4.
Even when the detectors are calibrated to minimize the streaking in the image, some errors from the calibration process are unavoidable. Each detector is sensitive to a slightly different spectrum of light, but they are all calibrated using the same calibration lamp with a broad, non-uniform spectrum. Since the scene spectrum is unknown, the calibration process assumes the spectrum of the calibration lamp and the scene are identical. The spectrum of the calibration lamp will usually be somewhat different than the spectrum of the scene being imaged, hence calibration errors will occur. Calibration errors also occur because the calibration process includes an incomplete model of the complete optical process and because the response function for each detector changes over time and operating temperature.
Streaking can be seen in uniform areas of an image acquired by a linear detector and become very apparent when the contrast of the image is enhanced. Calibration differences between the red, green, and blue detectors of color imaging systems produce streaks of varying colors in the composite color image. These streaks not only reduce the aesthetic quality of digital images but can impact the interpretability of features in the images. Streaking also severely degrades the performance of pattern recognition and feature extraction algorithms.
Streaks can be attenuated by reducing the contrast of the image or by blurring the image in a direction perpendicular to the streaking, but these methods degrade the quality of the overall image. Previously developed algorithms designed to remove the streaks while preserving the contrast and sharpness of the image assume that the streaks do not change over time or that the pixels near each other are strongly correlated. In general these assumptions are not true. The responsivity of each detector, and hence the magnitudes of the streaks, changes over time, therefore methods that remove fixed patterns of streaks will not always work. U.S. Pat. No. 5,065,444, issued Nov. 12, 1991, to Garber discloses a method of removing streaks from digital images by assuming that pixels in a predetermined region are strongly correlated, examining the pixels in the region, computes the difference between the pixels in the region, thresholding the pixel differences lower than a predetermined value, computes a gain and offset value from the distribution of differences, and uses the gain and offset value to remove the streaking. Methods that assume a strong correlation between pixels that are near each other, such as the one disclosed by Garber will interpret scene variations as streaks and produce additional streaking artifacts in the image as a result of attempting to remove existing streaks. FIG. 2a shows an image having streaks 2 and linear features 6 that are in the same direction as the streaks. As shown in FIG. 2b, the correction of the streaks 2 using the method taught by Garber remove the streaks 2, but results in additional streaking artifacts 8.
There is a need therefore for an improved digital image processing method for removing streaks in images.